Plot.plot({
width: width,
height: 420,
marginRight: 120,
color: {
legend: true,
scheme: "OrRd",
label: "Orders"
},
marks: [
Plot.lineY(pizza, Plot.binX({y: 'sum'}, {
x: "order_date",
y: "orders",
z: "name",
interval: d3.utcWeek,
tip: true,
stroke: "orders"
})),
Plot.lineY(pizza, Plot.binX({y: 'sum'}, {
filter: p => p.name == pizza_max_order.name,
x: "order_date",
y: "orders",
z: "name",
interval: d3.utcWeek,
strokeWidth: 3,
stroke: "red"
}))
]
})
heatmap = Plot.plot({
width: 720,
height: 300,
marginLeft: 90,
facet: {
data: pizza,
y: "pizza_name",
x: "size",
},
color: {
legend: true,
scheme: "RdBu",
label: "Orders"
},
marks: [
Plot.tickX(
pizza,
Plot.binX(
{
fill: "sum",
},
{
x: "order_date",
stroke: "orders",
interval: d3.utcWeek
}
)
),
Plot.frame({ stroke: "#aaa", strokeWidth: 0.5 })
]
})
Plot.plot({
width: 720,
height: 420,
facet: {
data: pizza,
y: "pizza_name",
x: "size",
marginRight: 90,
label: ""
},
color: {
legend: true,
scheme: "Pastel1"
},
marks: [
Plot.areaY(pizza, Plot.binX({y: 'sum'}, {
x: "order_date",
y: "orders",
fill: "category",
interval: d3.utcWeek,
tip: true
})),
Plot.ruleY([0])
],
y: {
tickFormat: d => ""
}
})
pizza
Type Table, then Shift-Enter. Ctrl-space for more options.
pizza
pizza_max_order = pmo[0]
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
